Characterization of the zinc cluster transcription factor Rds2 in «Saccharomyces cerevisiae» links glucose metabolism to antifungal drug resistance
Bibliographic record
Abstract
In Saccharomyces cerevisiae, zinc cluster proteins constitute the major family of transcriptional regulators for a variety of metabolic processes, yet the function of many are currently unknown. Previous studies have characterized Rds2 as a zinc cluster transcription factor that plays a role in antifungal drug resistance, but an exact mechanism is undefined. However, it has been established that Rds2 is a major regulator of gluconeogenesis. In this study, we aim to further mechanistically characterize the role of Rds2 in antifungal drug resistance. Microarray-based expression profiling of both wild type and ∆rds2 strains treated with ketoconazole indicates a greater than 2-fold decreased expression of genes involved in gluconeogenesis and the glyoxylate cycle, such as PCK1, YIG1, and MLS1, in cells lacking Rds2. Quantitative real-time polymerase chain reaction (qPCR) confirmed our microarray data. Furthermore, deletion of these metabolic genes confers azole hypersensitivity. Our preliminary results show that Rds2's role as a regulator of gluconeogenesis and the glyoxylate cycle is linked to its role in antifungal drug resistance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".